Interpretive Summary: There is a growing realization by agricultural researchers about the importance of root systems to crop traits such as nutrient and water acquisition and utilization, and tolerance to toxic metals in the soil. For example, with regards to tolerance to low phosphorous (P) in the soil, it is now known that root system architecture (RSA), which describes where the plant places different roots in the soil in 3 dimensions, plays a key role in the ability for the plant to efficiently acquire P in low P environments. Therefore, for the research detailed in this paper, we developed a novel system to: 1) grow root systems of cereal roots (rice) in transparent gellan gum nutrient media in special glass cylinders to fix their 3D RSA; 2) digitally acquire 40 2-D images of the entire root system of individual plants in a rapid manner, and 3) use custom designed software to reconstruct the 40 2D images into a 3-D model of the root system of individual plants, and then quantify nearly 30 different characteristics of RSA. This platform will now be used to genetically map RSA characters in order to clone genes underlying specific RSA genetic traits. Subsequently, this information will be used to determine the role of RSA in important crop traits in rice, sorghum and maize, such as more efficient utilization of limiting nutrients such as water, N and P, which in turn can be used by plant breeders to develop higher yielding cereal varieties based on superior root traits.

Technical Abstract:
A novel imaging and software platform was developed for the high-throughput phenotyping of 3-dimensional root traits during seedling development. To demonstrate the platform’s capacity, plants of two rice (Oryza sativa) genotypes, Azucena and IR64, were grown in a transparent gellan gum system and imaged daily for 10 days. Rotational image sequences consisting of forty 2-dimensional images were captured using an optically corrected digital imaging system. Three-dimensional root reconstructions were generated and analyzed using a custom designed software, RootReader3D. Using the automated and interactive capabilities of RootReader3D, 5 rice root types were classified and 27 phenotypic root traits were measured to characterize these two genotypes. Where possible, measurements from the 3D platform were validated and were highly correlated with conventional 2-dimensional measurements. When comparing gellan gum grown plants to those grown under hydroponic and sand culture, significant differences were detected in morphological root traits (p<0.05). This highly flexible platform provides the capacity to measure root traits with a high degree of spatial and temporal resolution and will facilitate novel investigations into the development of the entire root systems, or selected components of the root systems. In combination with the extensive genetic resources that are now available, this platform will be a powerful resource to further explore the molecular and genetic determinants of root system architecture.